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The present age is characterized by a very complex economic relationship among finance, technology, social needs, etc., which can be summarized in the word “sustainability.” The sustainable consumption and production policies represent the keys to realize sustainable development. But, the analysis of the carbon footprint data points out that the present economies are still carbon-consumption production. The reduction of greenhouse gasses emissions is based on a shift from fossil to renewable and bio-based industrial raw materials, with a related reorganization of the chains of the energy and manufacturing sectors. But, this requirement implies technological choices based on a sustainable measurement of their impacts on the ecological and economical contexts. So, social and economic requirements must also be taken into account by the decision-makers. Bioeconomy can represent a possible approach to deal with the requirements of the present time. But, new needs emerge in relation to sustainability. So, sustainable policies require new indicators, in order to consider the link among economics, technologies, and social well-being. In this paper, an irreversible thermodynamic approach is developed, in order to introduce a thermoeconomic indicator, based on thermodynamic optimization methods, but also on socioeconomic and ecological evaluations. The entropy production rate is introduced in relation to the CO2emission flows from human activities, and it is related to the income index, in order to consider the economic and social equity. This approach is of interest of the researchers in the field of econophysics, thermoeconomy, economics, and bioeconomy.

The energy consumption of sheep milk cooling systems (MCSs) was quantified in this study to provide original information filling a literature gap on the impact of sheep milk cooling on the energy and economic balance in dairy farms. Performance and energy monitoring tests were conducted simultaneously on 22 MCSs in Sardinia (Italy). The results determined the cooling time as a function of the performance class and number of milkings. The Energy Utilization Index (EUI) was applied to measure the energy required to cool down the milk and estimate the incidence on its price. The average EUI was 1.76 kWh 100 L−1 for two-milkings and 2.43 kWh 100 L−1 for four-milkings MCSs, whereas the CO2 emissions ranged from 998 to 1378 g CO2 100 L−1 for two- and four-milkings MCSs, respectively. The estimated energy consumption for the storage of refrigerated sheep milk was 0.12 kWh 100 L−1. The malfunctioning MCSs averagely consumed 31% more energy than regular systems. The energy cost for cooling accounted for 0.61% on the current sheep milk price in Italy. Based on the analysis, the reported EUI values can be used as a preliminary indicator of the regular operation of MCSs.

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios.

This review paper emphasised on the origin of hexavalent chromium toxicity in tannery wastewater and its remediation using novel Microbial Fuel Cell (MFC) technology, including electroactive bacteria, which are known as exoelectrogens, to simultaneously treat wastewater and its action in the production of bioenergy and the mechanism of Cr6+ reduction. Also, there are various parameters like electrode, pH, mode of operation, time of operation, and type of exchange membrane used for promising results shown in enhancing MFC production and remediation of Cr6+. Destructive anthropological activities, such as leather making and electroplating industries are key sources of hexavalent chromium contamination in aquatic repositories. When Cr6+ enters the food chain and enters the human body, it has the potential to cause cancer. MFC is a green innovation that generates energy economically through the reduction of toxic Cr6+ to less toxic Cr3+. The organic substrates utilized at the anode of MFC act as electrons (e-) donors. This review also highlighted the utilization of cheap substrates to make MFCs more economically suitable and the energy production at minimum cost.